code: def scale_linewidth_identity(
      name=None,
      breaks=None,
      labels=None,
      lablim=None,
      limits=None,
      na_value=None,
      guide="none",
      format=None,
  ):
      """
      Use this scale when your data has already been scaled.
      I.e. it already represents aesthetic values that can be handled directly.
      This will not produce a legend unless you also supply the breaks and labels.
  
      Parameters
      ----------
      name : str
          The name of the scale - used as the axis label or the legend title.
      breaks : list or dict
          A list of data values specifying the positions of ticks, or a dictionary which maps the tick labels to the breaks values.
      labels : list of str or dict
          A list of labels on ticks, or a dictionary which maps the breaks values to the tick labels.
      lablim : int, default=None
          The maximum label length (in characters) before trimming is applied.
      limits : list
          Continuous scale: a numeric vector of length two providing limits of the scale.
          Discrete scale: a vector specifying the data range for the scale
          and the default order of their display in guides.
      guide, default='none'
          Guide to use for this scale.
      format : str
          Define the format for labels on the scale. The syntax resembles Python's:
  
          - '.2f' -> '12.45'
          - 'Num {}' -> 'Num 12.456789'
          - 'TTL: {.2f}$' -> 'TTL: 12.45$'
  
          For more info see https://lets-plot.org/pages/formats.html.
  
      Returns
      -------
      `FeatureSpec`
          Scale specification.
  
      Notes
      -----
      Input data expected: positive numeric values.
  
      Examples
      --------
      .. jupyter-execute::
          :linenos:
          :emphasize-lines: 9
  
          from lets_plot import *
          LetsPlot.setup_html()
          data = {
              'x': [0, 1, 2],
              'y': [1, 2, 1],
              'w': [1, 3, 2],
          }
          ggplot(data, aes('x', 'y')) + geom_lollipop(aes(linewidth='w')) + \\
              scale_linewidth_identity()
  
      """
      return scale_identity(
          "linewidth",
          name=name,
          breaks=breaks,
          labels=labels,
          lablim=lablim,
          limits=limits,
          na_value=na_value,
          guide=guide,
          format=format,
      )
  
file_path: lets-plot/python-package/lets_plot/plot/scale_identity_.py
imports: from .scale import _scale
label_desc: Use image node_id 8 for calling a global function with example usage: scale_linewidth_identity(name, breaks, labels, lablim, limits, na_value, guide, format) and returns: scale_identity